Sponsors

  • Microsoft
  • Nebula
  • Google
  • SugarCRM
  • Facebook
  • HP
  • Intel
  • Rackspace Hosting
  • WSO2
  • Alfresco
  • BlackBerry
  • CUBRID
  • Dell
  • eBay
  • Heroku
  • InfiniteGraph
  • JBoss
  • LeaseWeb
  • Liferay
  • Media Temple, Inc.
  • OpenShift
  • Oracle
  • Percona
  • Puppet Labs
  • Qualcomm Innovation Center, Inc.
  • Rentrak
  • Silicon Mechanics
  • SoftLayer Technologies, Inc.
  • SourceGear
  • Urban Airship
  • Vertica
  • VMware
  • (mt) Media Temple, Inc.

Sponsorship Opportunities

For information on exhibition and sponsorship opportunities at the convention, contact Sharon Cordesse at scordesse@oreilly.com

Download the OSCON Sponsor/Exhibitor Prospectus

Contact Us

View a complete list of OSCON contacts

Personal schedule for Jonathan Seidman

Download or subscribe to Jonathan Seidman's schedule.

Data: NoSQL Databases
Location: B118-119
Siddharth Anand (LinkedIn)
Average rating: ***..
(3.70, 10 ratings)
Over the past few years, Netflix has migrated to the cloud. This talk details Netflix's transition away from relational databases and towards high-availability (NoSQL) storage systems. We rely on a combination of proprietary (e.g. SimpleDB and S3) and open-source (e.g. Cassandra and HBase) NoSQL technologies. Read more.
Data: Products and Services
Location: C125/126
Aurelian Dumitru (Dell, Inc)
Average rating: **...
(2.00, 1 rating)
In this session Dell will discuss the analysis of the data types suitable for transfer between Hadoop and EDW, EDW/Hadoop data lifecycle, Data governance between Hadoop and DBMS, and ETL performance tuning and best practices (i.e. Hadoop/DBMS connector, node and network designs, etc.) Read more.
Data: Roulette
Location: C123
Ted Dziuba (eBay Local/Milo.com)
Average rating: ****.
(4.64, 11 ratings)
What happens when you write data to disk? We'll explore everything between your programming language and the spinning platters - both optimizations and dangerous pitfalls. Read more.
Data: Hadoop
Location: C124
Arun Murthy (Hortonworks Inc.)
Average rating: ***..
(3.00, 4 ratings)
YARN is the next generation of Hadoop Map-Reduce designed to scale out much further while allowing for running applications other than pure Map-Reduce in a highly fault-tolerant manner. Read more.
Noah Pepper (Lucky Sort), Homer Strong (Lucky Sort)
Average rating: ***..
(3.18, 11 ratings)
We produce gorgeous LaTeX reports while harnessing the power of R on the backend. The data is pulled from our PostgreSQL database, the analysis and visualizations are fast and distributed thanks to Redis. We'll talk about weaving together open source tools to build powerful analytics reporting engines that rival the commercial alternatives. Read more.
Data: Big Data
Location: B118-119
Jay Kreps (LinkedIn)
Average rating: ****.
(4.11, 9 ratings)
The last few years have brought a wealth of new data technologies organized around horizontal scalability. This talk will cover the essential infrastructure areas: real-time stream processing, offline data crunching, large-scale data deployments and live serving. The focus will be on how these ingredients come together to enable innovative data-driven products at LinkedIn. Read more.
Data: Hadoop
Location: C123
Nicolas Spiegelberg (Facebook)
Average rating: ****.
(4.38, 8 ratings)
In November, Facebook launched a new version of Messages that combines chat, SMS, email, and Messages into a real-time conversation. Facebook relies on Apache HBase, a NoSQL-style database, for storing this real-time message data. This talk will elaborate on our decision process, system configuration, scaling issues, and advantages gained by choosing Open Source. Read more.
Josh Patterson (Cloudera)
Average rating: ***..
(3.75, 8 ratings)
Time Series sensors are being ubiquitously integrated in places like cell phones, environmental sensors, and the smart grid. As we scale out this type of data RDBMS systems strain to scale with the high insertion rates and real time query requirements. In this talk we introduce “Lumberyard” which is a scalable indexing and low latency fuzzy pattern searching time series data. Read more.
Philipp Janert (Principal Value, LLC)
Average rating: ****.
(4.00, 5 ratings)
Data Analysis is often wrapped in a bit of mystery, with specialized tools, fancy terminology, and difficult techniques. This tutorial takes a different stance: we will review a set of basic methods and techniques, which are nevertheless essential if you want to think about and understand data. Particular emphasis is placed on ways to gain insight through graphical methods. Read more.
Data: Analytics and Visualization
Location: Oregon Ballroom 203
Robin Anil (Google), Ted Dunning (MapR Technologies)
Average rating: **...
(2.75, 4 ratings)
This hands-on tutorial aims at learning the basics of the important machine learning algorithms in Mahout. It aims to help you get it up and running on a Hadoop cluster. Mahout is open source implementation of a collection of algorithms designed from ground up to sift through terabytes of data and help bring out important patterns which are otherwise not in the reach of standard tools. Read more.